sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
9e96d681e15d9b99ee62c6e084b5dcabe99076f6029710b8156c4e956c009abb | R | 8,116 | 270 | library(genio)
library(data.table)
library(magrittr)
library(dplyr)
library(devtools)
library(R.utils)
library(susieR)
library(ggplot2)
library(glue)
### Credit: Xiangyu Zhang ###
args = commandArgs(trailingOnly=TRUE)
gene <- args[1]
gwas <- args[2]
celltype <- args[3]
weight <- as.numeric(args[4])
namelist <- rea... |
13f0976595e6cefb5eef65a85eed2c13109c34a062f47b39f4f114e515ef8bb8 | R | 8,119 | 265 | srun --nodes=1 --ntasks-per-node=1 --pty bash -i
sif=/data/dcibioinformatics/sifs/dcibioinformaticsR-v2.1.sif
wd=/data/dcibioinformatics/Anders/MelBrM_rerun
singularity exec \
--containall \
--no-home \
--bind ${wd}:${wd}:rw \
${sif} \
R
# -----------------------------------------... |
e13ed856ac47a5fef2e8d0c323c780721379ec39257cd0d92c9b4c13f6d70605 | R | 8,159 | 225 | # L2/3 IT neurons
####################################################
# Cux2 Cre
# Experiment ID: 294434161
# http://connectivity.brain-map.org/projection/experiment/294434161?imageId=156742363&initImage=TWO_PHOTON&x=19348&y=14762&z=4
#
#
# URL_projection_density =
# "http://api.brain-map.org/grid_data/download... |
8e7de332782e5294826f93f4b3d702087ddafdd8cbcb0d889720071a76ee7820 | R | 8,161 | 174 | # UMAP plotting for samples, markers and clusters
# adapted from SIMPLI plotting functions
# Input data:
# - clustered_cells.csv (SIMPLI output)
####### SETUP from SIMPLI #######
library(data.table)
library(uwot)
library(ggplot2)
#install.packages("qs", type = "binary")
library(qs)
#source("scripts/Plot_Functions.R... |
d1743368bc0de6a3783e81c05ed6890a0ca992b5042169a320916a80d44433d6 | R | 8,162 | 167 | #This is R code for a practice search in GEO
#2026-06-22
#Megan Hagenauer
########################
if (!require(BiocManager, quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("GEOquery")
library(GEOquery)
#Come back to protocols.io and add quotes to "BiocManager" and "GEOquery"
#protocols.io:... |
765bc40eae9232013107b3123f979289de256656838501b03a563d9b26103f7d | R | 8,164 | 126 | ## Overlap between Tg2576, TauCortex, and human data across the main cell types ##
rm(list = ls())
library(dplyr) # dplyr_1.1.4
library(ggplot2) # ggplot2_3.5.1
library(ggVennDiagram) # ggVennDiagram_1.5.2
options(stringsAsFactors = FALSE)
options(width=120)
set.seed(1)
# Thy-Tau22 (17m)
# load("./results/files/TauC... |
59103d50b070bb2ffae297af03ff769a102c3f1a26a6c79a36b06b4901cd5fea | R | 8,170 | 288 | #!/usr/bin/env R
# Author: Sean Maden
#
# Get RMSE calculations compatiable with test datasets.
#
#
#
labelsVectorFromFilter <- function(filterLabels, filterConditions,
labels = c("sample.id", "condition.id", "replicate.id")){
# labelsVectorFromFilter
#
# Bind filter term labe... |
b4ae3d32d3bb1609659dfa3afb3f040094948eabf275b6146a6c4a513740dbc4 | R | 8,194 | 245 | ---
title: "Coeff vs DA corr"
output: html_document
editor_options:
chunk_output_type: console
---
# motus
```{r}
library(ggplot2)
library(dplyr)
library(readxl)
df.cross<-readRDS("/metaG//R_analyses/Taxonomy/RDS/df.DA.rds")
df.pos.neg<-readRDS("/metaG//R_analyses/Taxonomy/RDS/Ridge_df.pos.neg.rds")
# select only ... |
8652f68f631d5e8e58e88f22c41e99064f94c5242557e47828a03f060d4a3b87 | R | 8,197 | 187 | # R Corbett 2023
#
# Generate alluvial plot for PBTA ancestry project
# load libraries and set directories
library(data.table)
library(tidyverse)
# library(ComplexHeatmap)
# library(RColorBrewer)
# library(circlize)
library(colorblindr)
library(ggpubr)
library(ggalluvial)
library(cowplot)
root_dir <- rprojroot::find_... |
91d4b92bc967368ffae64ac8455b65807791a337f9839dc175949fb129454627 | R | 8,228 | 198 | # creates final plots for the Simulations of the PRS GXE project
# grab command line arguments
args = commandArgs(trailingOnly = TRUE)
print("Arguments received:")
print(args)
if(length(args) < 2) {stop("not enough Arguments received")}
baseLoc = args[1]
outputLoc= args[2]
plotName= args[3]
# Debug vars
# baseLoc ... |
cb733d24b4111c83330bbc9b20ef34c498f2c97ff1b470ac22ace1bebf444c1f | R | 8,231 | 211 | #Script to create Figure 2
library(Seurat)
library(tidyverse)
library(gdata)
library(slingshot)
library(RColorBrewer)
library(sctransform)
library(glmGamPoi)
library(cowplot)
set.seed(1000)
#Huwe1 data ----
#Script to create Figure 1 - Huwe1 data
#pseudotime construction using PCA for Huwe1 NSCs
load(file = "1st_sub... |
603b4961499007981cad6af4296a9933390f1bca6ed38b6a0a5c987308f7b631 | R | 8,246 | 179 | # generate T4b gallery and save to pdf ----------------------------------------
# choose nb via nb_ind
# align to meridian by mapping ref points to med via np
library(natverse)
library(tidyverse)
source("eyemap_func.R")
load('data/T4_gallery.RData')
load('data/hexnb_ind_dist.RData') # in 'eyemap_lens_med_lop.R'
nb... |
e95ac0b8da8390a5327aa6dcdf219e0da535caf59801864c127f5b8307e55875 | R | 8,247 | 210 | ##############################################
# Giotto Benchmarking - Kidney 10x Visium
# Authors: Chandrima Modak, Mauminah Raina
##############################################
#Load required packages
library(Matrix)
library(Seurat)
library(Giotto)
library(GiottoData)
library(dplyr)
library(readxl)
libra... |
37c500dd1484caf90ad374c7442574fdcb964a6670ff08b1536544084ed41042 | R | 8,248 | 146 | #!/usr/bin/env Rscript
options(stringsAsFactors=F)
## load R libraries
#library(SAIGE, lib.loc="../../install_dir/0.38")
#library(SAIGE, lib.loc="../../install_dir/0.36.6")
#library(SAIGE, lib.loc="/net/hunt/zhowei/project/imbalancedCaseCtrlMixedModel/Rpackage_SPAGMMAT/installSAIGEFolder/0.44.6_Neff")
#library(SAIGE,... |
ff0683b662d6a8defaf11194f7df1409d33d6c46a5715e86f189f72f5d84602f | R | 8,255 | 235 | ---
title: "Figure 5"
author: "Sang LIU"
date: "`r Sys.Date()`"
output:
html_document:
code_download: TRUE
theme: united
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE)
```
## Load packages
```{r}
library(circlize)
library(nat)
library(ggpubr)
library(reshape2... |
c5702feae8fba30c4d1cba4f241cb07c141796eda619ef376bab8ca1af34b57c | R | 8,286 | 177 | #!/usr/bin/env R
# Author: Sean Maden
#
# Deconvolution plots script. Sourced by notebook for Ybulk experiment with 4 identifier conditions in the experiment.
#
deconvo_plot_statistics <- function(dfp1){
# postprocess dfp1
dfp1$s.fraction.neuron.glial <- dfp1$s.neuron/dfp1$s.glial
dfp1$s.fraction.neuron.glial.d... |
098fa429c302d451a124c688765dbc9dba7f90b98393bed622e8eb2c4c3f649c | R | 8,298 | 138 | ---
title: "6. FAQ"
output:
rmarkdown::html_vignette:
toc: true
vignette: >
%\VignetteIndexEntry{FAQ}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, eval = FALSE)
```
# FAQ
Below is an FAQ
## Hardware recommendations
Be... |
0129e8f23a3443356c9c3832f018def4825eb9a5f5ebfd1dc22a71e2ea90160f | R | 8,302 | 133 | ---
title: "EDCS access and merging of TSV files"
author:
- Petra Hermankova^[Aarhus University, petra.hermankova@cas.au.dk, https://orcid.org/0000-0002-6349-0540]
date: "`r format(Sys.time(), '%d %B, %Y')`"
output:
html_document:
theme: united
toc: yes
toc_float: true
number_sections: true
toc_de... |
a81e09f98c8058658c3925ebf7372f4d65d98e75c6e4abdf7abf73f7fc4f2e9d | R | 8,316 | 298 | ---
title: "Plate reader growth curves of GAT201 targets in RPMI"
author: "Liz Hughes & Edward Wallace"
date: "16/05/2023"
output:
html_document:
toc: yes
toc_depth: 2
---
```{r call_shared_functions_formatting, child = "shared_functions_formatting.Rmd"}
```
# Summary
Plate reader growth curves of GAT201 t... |
e4d23c9f03da22aaa38564beae10a54cb7c2f44ecfe063bf2475e179104e29af | R | 8,328 | 265 | ---
title: "Compare Coefficient of variation between individuals"
author: "Joyce Hsiao"
date: 2015-10-16
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
library(knitr)
opts_chunk$set(message = ... |
4f5eab5f3c79ecff1f1c916e69dfe0f24d2939f1381fe628fc31fa243263efb6 | R | 8,360 | 155 | rm(list=ls())
args <- commandArgs(TRUE)
DATATAG <- args[1] # "Chinese_AgeT_Global"
Indexflag <- args[2] # TotalGM
## COMMON LIBRARIES AND FUNCTIONS
source("100.common-variables.r")
source("101.common-functions.r")
source("300.variables.r")
source("301.functions.r")
## SCRIPT SPECIFIC LIBRARIES
## SCRIPT SPECIFIC F... |
28e5ba1f22fd6f71fbd46917e7a6f8b4563a14cca9003abe64f3162ac420acf0 | R | 8,367 | 198 | library(dplyr)
library(readxl)
library(ggplot2)
library(ggrepel)
library(DOSE)
library(enrichplot)
library(clusterProfiler)
library(org.Mm.eg.db)
setwd("")
# Figure_5b, bar plots of identified and quantified proteins, respectively
{
rm(list=ls())
Obj.list = readRDS(file = "ct_dataset_01.rds")
temp.df = Obj.list... |
babf178c149c4e4e60b7cbd206c909677d78924cb2af3c9c1ada814399c9565e | R | 8,406 | 222 | library(tidyr)
library(dplyr)
library(data.table)
library(parallel)
library(ComplexHeatmap)
library(circlize)
library(viridis)
library(ggplot2)
workingDir <- '../2024_02_29_multiVelo/'
dataDir <- '../2024_02_29_multiVelo/data/'
print("Reading in state files")
stateFile_case <- fread(file.path(dataDir,'PFC_vs_VIS_Maca... |
6cc8b7f3740d1a0b74edd6c5b3944e15090c1a53eef008be299697be06ebe6f9 | R | 8,422 | 201 | #Example Code for Comparing Two Sets of Differential Expression Results
#Megan Hagenauer
#2025-06-11
###############
#Reading in the differential expression results for the two datasets:
#Set your working directory to where your differential expression results are stored
#This can be done using the GUI: "Session"->"... |
c72fca88557d26daa4676dd8df19dcf77462b9d6ca66d0790cba81abfe06e967 | R | 8,424 | 299 | ---
title: "RT-qPCR 2022-10-14 GAT201 complemented strains and targets"
author: "Liz Hughes & Edward Wallace"
date: "07/10/2022"
output:
html_document:
toc: yes
toc_depth: 2
---
```{r call_shared_functions_formatting, child = "shared_functions_formatting.Rmd"}
```
# Experimental Design
This experiment was ... |
b7fa790d64b0ac39efb199279fc84a8b9fa42b0ffab2bafcec1b5f91b5329038 | R | 8,435 | 207 |
#Determining which mouse genes align to which rat genes
#Gene Ortholog Database:
#Downloaded from Jackson Labs July 27, 2023
#https://www.informatics.jax.org/downloads/reports/HOM_AllOrganism.rpt
#Another good source of ortholog information is HCOP:
#https://www.genenames.org/tools/hcop/
#I should note: when deter... |
48ad47eec0bb8ede501a3d1c4a234449f01e398d309dc08aaf6b8532a742c9c5 | R | 8,452 | 227 | ## Comparison with retro-seq data in vmPFC (Liqun LUO, Cell, 2020)
## 18 projection subtypes in PL/ILA/ORBm
Label_Subtype_mPFC_PT = c(57, 60, 62, 64)
Index_mPFC_PT = base::intersect(which(Label_Subtype_PFC %in% Label_Subtype_mPFC_PT == TRUE),
which(PFC_projection$BrainRegion %in% c("PL... |
4a534c517e6f4a2e622ac3c5e0e1f3e1829bb5bc2383f6a3922963da4c05e0b5 | R | 8,456 | 280 | ---
title: "Compare Coefficient of variation between individuals"
author: "Joyce Hsiao"
date: 2015-10-16
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
library(knitr)
opts_chunk$set(message = ... |
f508a5fb947850d2daa2b58f3775b278bb117040e3acb914011a2192d12387c7 | R | 8,462 | 283 | ---
title: "Explore distribituions"
author: "Joyce Hsiao"
date: 2016-02-01
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
library(knitr)
opts_chunk$set(message = FALSE, warning = FALSE, eval... |
724e2f85fb248130b71a1b6dba2e656f44bf7e7b1e92be15270ccf0746c1a449 | R | 8,470 | 223 | #Sample code for MetaData extraction for Gemma datasets, part2: Filtering
#Megan Hagenauer, Jun 27 2024
############
#This code has not been cleaned up, fully annotated, functionalized, and made easily generalizable
###############
library(gemma.R)
library(dplyr)
###############
#After we've decided on our search... |
b510be726903dbb4c69a3abf1b2adea61bede33bb22305f78cedf30c95a382d0 | R | 8,492 | 189 | gen_histograms_spec_beh <- function(dir_in, hem, other_dat){
# generate histograms for key behavioral variables
ids <- read.table(paste0(dir_in, '/', hem, '_final_ids.txt'))
colnames(ids)[colnames(ids) == 'V1'] = 'id'
other_dat <- inner_join(ids, other_dat, by = 'id', multiple = 'first')
tps <- c('inf', 'tod', 'pre... |
ad491283294800f685d54a4d104d1b75437018f3d6ce786782c0e8c5718e5b98 | R | 8,525 | 286 | # calculate time passed
get_times <- function(data) {
data_bl <- get_uniq_data(data)
for (i in seq_len(nrow(data_bl))) {
subj <- data_bl[i, "SubID"]
bl_age <- data_bl[i, "chron_age"]
is_subj <- (data$SubID == subj)
data[is_subj, "time"] <- data[is_subj, "chron_age"] - bl_age
}
return(data)
}
#... |
3f6b79686f143cf0304e310f02c016cf4383e29009483cf5a0b227bcc6785725 | R | 8,540 | 295 |
Index_MOs_PT = base::intersect(which(PFC_projection$BrainRegion == "MOs"),
Index_PT)
NumNeuron_MOs_PT = length(Index_MOs_PT)
## main subtypes
pie(table(Label_Subtype_PFC[Index_MOs_PT]))
Index_MOs_PT_Main <- Index_MOs_PT[Label_Subtype_PFC[Index_MOs_PT] %in% c(56, 53, 58)]
## sear... |
0e4839172121e37ceaf58327ed9afc1c6003be1f40ff2cbc0b633ef67f38539d | R | 8,546 | 178 | #This is code that provides functions for aligning our differential expression results across datasets
#Megan Hagenauer July 25 2024
#Goals:
#Each dataset has differential expression results from a slightly different list of genes
#Depending on the exact tissue dissected, the sensitivity of the transcriptional profili... |
62344911edd3a2fa745af22305fe8ec59c25b89bce2d8ed9cd970616ac19cd23 | R | 8,558 | 159 | #Fig 4b
phee_count<-phee.analysis%>%
dplyr::mutate(subject= factor(subject))%>%
#dplyr::mutate(wks= factor(wks))%>%
dplyr::mutate(timebin= factor(timebin,
level = c("1min","2min",
... |
f64e90d7f06c871d9d7abb96ed1246d15da79acd3e39a98a541afb6f8909896a | R | 8,564 | 250 | #' Proprocess a trial results tibble
#'
#' This function takes a trial results tibble as generated by `read_study_data`
#' and adds a number of trial-level variables and summary statistics used for
#' quality checks and analyses. Assumes that `threat_appear_time` has already
#' been computed (as this can be study- and ... |
d1db1248f4cb4f058efa736b8a63ec5867221260322b75a9820209caec760243 | R | 8,580 | 211 |
libv <- c("snow", "dplyr", "parallel", "doParallel", "lute", "dplyr")
sapply(libv, library, character.only = T)
#------
# setup
#------
# helper functions
# get series of s cell size factors (THIS SCRIPT, AND A FEW OTHERS)
dfs.series <- function(s.glial.series = seq(1, 10, 0.2)){
s.neuron.series <- rev(s.glial.seri... |
a632a62aeb1d5bb08d9d6dbe2b421b5033b1cc62b0f11660daf8786422876284 | R | 8,615 | 183 | ---
title: Accessibility, Methylation, and 5hmC Boxplots
---
```{r warning=FALSE, message=FALSE}
library(ggplot2)
library(gghighlight)
library(RColorBrewer)
library(tidyverse)
library(DESeq2)
library(egg)
peak_assignment<- read_tsv("/Users/lindsey/Desktop/Hodges_Lab/ATAC-me\ NPCdiff/NPCDiff_ATACme/New_timepoints/data... |
eb361013bba998b29ff0b4d6d025c7b73dbfb21f06055dd1ed2c2aadc959e29e | R | 8,625 | 209 | #Determining which mouse genes align to which rat genes
#This code was updated April 25, 2024
#Gene Ortholog Database:
#Downloaded from Jackson Labs April 25, 2024
#https://www.informatics.jax.org/downloads/reports/HOM_AllOrganism.rpt
#Another good source of ortholog information is HCOP:
#https://www.genenames.org/to... |
6ace6cfc8d1fd88d728c6d24515226e1cdc1480214ec89d1cd96fa8f3bdfc570 | R | 8,627 | 211 | rm(list = ls())
library(plotly)
library(tidyr)
library(ggrepel)
library(gtools)
library(data.table)
library(gplots)
library(useful)
library(locfit)
library(Matrix)
library(dplyr)
library(ggplot2)
library(Seurat)
library(Rmagic)
library(readr)
library(phateR)
library(viridis)
#library(DoubletFinder)
library(harmony)
lib... |
62f7b4a475390cad36555025b772f39d3f8ff5f878216b25dcbbf1367c31f5a6 | R | 8,653 | 224 | ---
title: "Effect of sequencing depth on UMI counts from Islam et al., 2014"
date: 2015-09-24
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
opts_chunk$set(cache = FALSE)
```
Does the sequenc... |
2226f8e3d34ca3096caddcfeea89d7367ad871dc3aee6baf61c8a17ad423e5e6 | R | 8,686 | 254 | library(shiny)
library(shinydashboard)
library(shinyalert)
library(dplyr)
library(purrr)
library(ggplot2)
library(echarts4r)
library(MetBrewer)
library(forcats)
library(DT)
library(zip)
library(reticulate)
library(Rcpp)
library(reshape2)
library(colormap)
library(patchwork)
library(qgraph)
library(devt... |
f79f9f6bf1720ce7044721907f01266cfb84749ae617d55198782b65f43d3ccc | R | 8,686 | 302 | # Created on Wed May 12 00:03:40 2021
# Name: synaptic_gradient_3d.R
# Purpose: Colors neurons skeletons based on the synaptic gradient
# Author: Andrea Vaccari (avaccari@middlebury.edu)
#
# Generates 5 plots:
# - the first two plots are gradients for single posts based on the number of
# synapses with pre. The c... |
d0ddc9bec7c1934fc4f3b6c5d84911d1508ddd018807551c34bc70125515fd27 | R | 8,693 | 131 | ---
title: DESeq2 for Differential Expression
---
```{r warning=FALSE, echo=FALSE, message=FALSE}
library("tidyverse")
library("DESeq2")
library("ggplot2")
library( "genefilter" )
library("pheatmap")
library("cluster")
library("factoextra")
library("RColorBrewer")
library(viridis)
```
```{r}
setwd("/Users/lindsey/Desk... |
dde09dfff507d4e71a5fd4ba8234889b97b998488adbbdd05cd20c9bbc250d83 | R | 8,701 | 167 | # -*- coding: utf-8 -*-
#Author: Xiaoyan Wang
#Copyright (c) 2024 __CarlosLab@CCMU/CIBR__. All rights reserved.
FB_colors <- c("Neuron" = "palevioletred2", "Astrocyte" = "olivedrab2", "Microglia" = "mediumpurple1",
"Oligo" = "skyblue", "OPC" = "chocolate1")
### cell type markers for forebrain, interbrain ... |
b0be87f96cda3eff23f46b6f189e73f5fae729daeb6ea04cd3682dbbeb6f4690 | R | 8,705 | 394 | ---
title: "Cell type proportion summaries"
author: "Sean Maden"
date: "2023-09-21"
output:
pdf_document: default
html_document: default
---
Cell type proportions from snRNAseq and RNAscope.
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
libv <- c("dplyr", "ggplot2", "GGally", "ggcorrplot")
sapply... |
7f7293516336cfcdc16e3d6f80daa34a752b945aee3cac994338f489f5b05642 | R | 8,708 | 262 | ## Test some edge cases not covered in the example files ##
# Test for error when file contains no "START" messages
test_that("test_err_on_no_data", {
expect_error(read.asc(I("hello\nthere")))
})
# Fully test raw colname generating code
test_that("test_raw_colnames", {
# Test monocular first
info <- lis... |
251f959267d52ad11226257ecbf299efe2aea01100d11e5f54b8e2a5d7e464e8 | R | 8,748 | 249 | sif=/mnt/data1/public/singularity/dcibioinformaticsR-v2.1.sif
wd=/mnt/data1/workspace/Anders/MelBrM
rtmp=/mnt/data1/workspace/Methods/Containers/MissingPackages/v2.1:/rtmp
singularity exec --containall --no-home --bind ${wd}:${wd}:rw --bind ${rtmp} ${sif} R
library(tidyverse)
library(openxlsx)
library(DESeq2)
library(... |
323349a439a92fcf8cca312386276df56848bd3df923fb2621b5019d5e93b511 | R | 8,756 | 315 | ---
title: "Load Data"
output:
html_document: default
pdf_document: default
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE,message = FALSE)
```
## Load multiomics package
```{r load package}
library(multiomics)
```
## Load TMT Nothobranchius data
Use the function `LoadMultiExperiment` to org... |
191f3fe2cf7bf491999178fdc6a3eabcf237b5b5ac7bad32f13c0e6ed2ef925a | R | 8,774 | 211 | getwd()
setwd(directory)
library(DESeq2)
# cannot load pheatmap although package installed apparently, load heatmap instead
# read what the fehler says, execute it (delete some folder from documents bla bla) and try to install again, works!
install.packages("pheatmap")
library(pheatmap)
install.packages("ggplot... |
dc6964bb742a228810f3c6538186287f0f210a3b772195807e44288e570f1976 | R | 8,796 | 153 | #This code document includes the code for a function that is designed to run a basic meta-analysis of Log2FC and sampling variance values using our previously generated objects MetaAnalysis_FoldChanges & MetaAnalysis_SV
#Megan Hagenauer
#Original version: July 25 2024
#In response to reviewers' comments, this function ... |
710b8f3feca27496f039c03b3e6dd9c0862e7def1cd0f84a300b68960d5390ce | R | 8,861 | 212 | #!/usr/bin/env Rscript
#### Adjust BP, other parameters using childsds package
#Setup
library(childsds)
#Define a function for printing the date, time and what we are doing:
print_now <- function(statement){
#Function that takes a statement and prints the date and time
print(paste(statement, Sys.time(), sep = ': ... |
8bfbcee81f5dc654e6edefd15bd2413414abe6b278682ac7dbd877b69306ee35 | R | 8,901 | 264 | ---
title: "Windowing Raw Sample Data"
author: "Austin Hurst"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{Windowing Raw Sample Data}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r results="hide", message=FALSE}
# Import libraries required for t... |
046d67451f3e2bb9e44fa937ceeb7447a87d11a9c07061fcbff9b01c046dce26 | R | 8,903 | 207 | ---
title: "3. Scripting & notebooks"
output:
rmarkdown::html_vignette:
toc: true
vignette: >
%\VignetteIndexEntry{Scripting and scaling up}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r, include = FALSE}
options(width = 300, rmarkdown.html_vignette.check_title = FALSE)
knitr::opt... |
5d69f6d52e4086f926640eceb4b54dad6bf45704c2d2b08c95481e098b281ec1 | R | 8,906 | 175 | ---
title: "Summary visualisation of cingulotomy cell densities"
output:
html_document:
df_print: paged
---
```{r setup, include=FALSE}
library(tidyverse)
library(here)
library(forcats)
library(ggdark)
options(scipen=999)
set_here(path='..')
theme_set(dark_theme_bw(base_size = 14) + theme(legend.... |
c952e8b4f5a499095273318efbfbce1ef0a1016a8c04eb192967afb4cf0a13e0 | R | 8,932 | 234 | ---
title: "Data transformation"
date: 2015-09-30
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
opts_chunk$set(fig.width = 8, fig.height = 8)
```
```{r packages, message=FALSE}
library("ggplo... |
1fede44672876cd6b311e472f3e36ab123662e69c4e58096afb43f0454231dd7 | R | 8,957 | 243 | ---
title: "Tracking down bug in reads to molecules conversion - Attempt 02"
author: "John Blischak"
date: 2015-02-19
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
opts_chunk$set(cache = TRUE)... |
38ad2211c798ac8ac1c5bde9ffd924b177578f9dfb52abaf9a99b91355e8a177 | R | 8,978 | 261 | ---
title: "Quality control plots"
author: "PoYuan Tung"
date: 2015-10-21
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
opts_chunk$set(cache = FALSE)
```
## Input
```{r packages, message=FAL... |
affe85043402ef99f829430a5ee45b33e6bee77f3d0e3effce51ac5d81004c8c | R | 8,989 | 203 | #code for sup figure 7
#import libraries
library(ggplot2)
library(REdaS)
library(patchwork)
library(nlme)
#Panels B-D
#load data
nonz_data <- read.csv("C:/Users/mbasn/Dropbox/Manuscript-Basnak/Nat Neurosci Aug 2024 revision/zenodo/Ext_data_fig_7_analysis/all_movement_data_bar_trial_including_rest_10_sec... |
7f27aac18ada41e7f6eb708a0cd2dba8d11ba73d322aca8722b9997ba1c480a5 | R | 9,003 | 211 | #' Create Excel header style.
#'
#' Create Excel header style. Depends on the \code{openxlsx} package. All arguments have default values and are optional to allow parameters to be modified.
#'
#' @param fill Header foreground fill.
#' @param color Header font color.
#' @param font Header font name.
#' @param siz... |
1291ca2b4cd6a71fc392db15f07dafae48def2b70c30a7f3232d19312584bb67 | R | 9,051 | 172 | #Dealing with a lack of Summarized Experiment object in Gemma
#Megan Hagenauer, July 18, 2023
#Dataset: GSE85136 - for Christabel
#This is an RNA-Seq dataset
#It isn't playing well with the summarized experiment or expression set dataset objects
rm(SummarizedExperiment)
SummarizedExperiment<-gemma.R::get_dataset_obje... |
91c41cdc21282cd638a2f3a9272ffafd0d80e526e012af60b699a1a8916bcb16 | R | 9,053 | 191 | #Example pipeline for aligning our results across datasets:
#Megan Hagenauer
#July 25 2024
############
#Goals:
#Each dataset has differential expression results from a slightly different list of genes
#Depending on the exact tissue dissected, the sensitivity of the transcriptional profiling platform, the representat... |
f53edee7fdda4751b58d29e1cf8808654d93585752cd75689bdb86b9e14b7683 | R | 9,064 | 316 | ---
title: "Ordering effect of the capture sites, all genes CPM normalized"
author: "Joyce Hsiao"
date: 2015-10-02
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
```
## Goal
We investigated p... |
b0d0f8c88839aee79045f277f7de0ec603c9c2076c83caee1e39014e5a7a8edd | R | 9,086 | 273 | ---
title: "BASiCS - 40,000 iterations"
date: 2015-08-10
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
```
We analyzed our single cell data with [BASiCS][] developed by [Vallejos et al., 2015... |
04177e87d375e93f39b1b0bbf42a404439185b6021dc960bc0af41d90278f5ca | R | 9,117 | 212 | ---
title: "Extended Data Figure 4"
author: "Sang LIU"
date: "`r Sys.Date()`"
output:
html_document:
code_download: TRUE
theme: united
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE)
```
## Load packages
```{r}
library(nat)
library(reshape2)
library(ggplot2)
l... |
42fd5c52a974d3a3de814b82f0f71674e2c026c8cd7c16011d9b8eb827fdb55f | R | 9,150 | 318 | ---
title: "KO DA"
author: "SRomano"
output:
html_document:
toc: yes
editor_options:
chunk_output_type: console
---
# Load packages
```{r setup}
list.of.packages <- c("tidyverse", "ggplot2", "RColorBrewer", "meta", "genodds")
new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,... |
1681055af92d7c2078f8b76d9a9a5edfa36cb511aa287599a62afc1b1687a209 | R | 9,186 | 205 | ---
title: "Pseudobulk k2 with and without cell size rescaling, cohort1"
author: "Sean Maden"
date: "2023-09-17"
output:
pdf_document: default
html_document: default
---
```{r setup, include=FALSE}
libv <- c("here", "nlme", "lute", "ggplot2", "gridExtra",
"dplyr", "ggforce", "MultiAssayExperiment", "Sin... |
b32f0dc563539cef34862d45cd7a94dc5a21adff47a071fc0f0da2490fa5574c | R | 9,189 | 267 | # MD subdivision
library(stringi)
library(matrixStats)
PFC_projection = read.csv(file = "/home/admin/Documents/YanLab/Task_Local/PFC_single_neuron_projectome/data_preparation/PFC_neuron_projection_v3.csv",
header = TRUE, sep = ",")
Index_PT_CT = which(PFC_projection$Type %in% c("PT", "CT") ... |
e824d930ffd8acf719e4efac6c3f41c78f0cb4566e9e86adeb4e15258f1eccfb | R | 9,189 | 327 | ##### imports #####
devtools::document()
devtools::load_all()
box::use(
eplp = escottpricelabpipelines[
simulate_y, read_config,
binary_from_liability,
upsample_individuals_independently,
simulate_e2_e4,
downsample_individuals
],
jntr = janitor[clean_names, row_to_names],
dplyr = dplyr[filte... |
0b4829dbd6ee9d1f2939663c7f72552b591aa7f584eb4476127443952084deaa | R | 9,211 | 219 | brain_region_ggseg <- function(meas, hem, dir_in, indx, fdr_cor){
# Plots FreeSurfer-labeled brain regions using the ggseg package
# For questions: theodore_turesky@gse.harvard.edu
if (hem == 'lh'){
hemi = 'left'
} else {
hemi = 'right'
}
# Specify color(s) to use
labels_colors <- graph_labels_colors(meas)... |
94c7597906fcbd6b4303d2a8218af33f19678ba337f4c3a020b3eafb83d3c781 | R | 9,222 | 257 | ###################################################
###################################################
#### EMBL-EBI Dementia Course ####
#### Biomarkers and PRS ####
#### Emily Simmonds & Valentina Escott-Price ####
#### UKDRI at Cardiff University ####
#### 10th April 2024 ####
##... |
3cef1af353ac451e787e266ac243269ab7aa871688788e0ee349bbd50aca0578 | R | 9,244 | 222 | ---
title: "BASiCS analysis of Mouse ESC dataset"
date: 2015-09-29
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
opts_chunk$set(cache = FALSE)
```
The first half of the analysis is the data c... |
8d7754469a5b11013a02c0ade85c747bca6ce2ecea3e02b84f2eec7451aded7b | R | 9,334 | 258 | library(tidyr)
library(dplyr)
library(data.table)
library(parallel)
library(ComplexHeatmap)
library(circlize)
library(viridis)
library(RColorBrewer)
library(patchwork)
library(ggplot2)
workingDir <- '../2024_02_29_multiVelo/'
dataDir <- '../2024_02_29_multiVelo/data/'
print("Reading in state files")
stateFile_case <-... |
2c6081b5bd282d2b344d762a605806faab253436ceb9676b043bb219d748a94c | R | 9,349 | 264 | # see Fig_4.R for ED Fig.7A, ED Fig.7B, ED Fig.7E, ED Fig.7F
# ED Fig.7D, size, T4d on eye --------------------------------------------------
LL <- 4 # choose type
# - eye
com_xyz <- as.matrix(lens_type[[LL]][, c("comx","comy","comz")])
v0 <- as.matrix(lens_type[[LL]][, c("x0","y0","z0")])
v1 <- as.matrix(lens_type... |
f09b999ad1754937304bfcff67b99286dd44ef289543cf61679681985c359be5 | R | 9,356 | 237 | ---
title: "Filter genes and low-quality single cells"
date: 2016-01-18
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
opts_chunk$set(fig.width = 8, fig.height = 8)
```
```{r packages, message... |
705dbc93208abd233e34697df554b5f15f5d513da2e982f52726b7cfa6713dc4 | R | 9,361 | 99 | ---
bibliography: refs.bib
---
```{r chunk-options, include=FALSE}
source("chunk-options-paper.R")
```
## Supplementary Figures
![**Supplementary Figure `r fig_supp_qc`. Removal of low quality samples.**
Violin plots of the total read-counts of ERCC spike-in controls in (A) and the total molecule-counts in (B) in si... |
37eda6eb1b4cd9a3946c875f3c66f3f5002590d1c9b9f3251aab2254eeecd200 | R | 9,370 | 303 | ---
title: "04_simulations"
author: "Sean Maden"
date: "2023-11-22"
output:
pdf_document: default
html_document: default
---
Results from pseudobulk simulations using Plasmablast and Non-plasmablast cell
proportions from Monaco et al 2019.
```{r setup, include=FALSE}
libv <- c("lute", "ggplot2", "gridExtra", "re... |
615db2d136128e3f92d5c62d876a57832f4a0bbea98f0d947592a0e24b961089 | R | 9,376 | 228 | #!/usr/bin/env Rscript
# Aaron M. Allen, 2019.06.06
library(Seurat)
library(dplyr)
library(future)
plan("multiprocess", workers = 8)
plan()
NumberOfCCAs <- 45
nGeneLowCutOff <- 200
nGeneHighCutOff <- Inf
nUMILowCutOff <- 1200
nUMIHighCutOff <- 10000
ClusterResolution <- 12
MitoLowCutOff <- -Inf... |
ee3c9ecac797e24c5a866eeefe0caeaed501f9f03b22509557813b3c90d86e5c | R | 9,376 | 224 | ################################################################################
#################### EMA Microglia GSEA Bubbleplot #############################
################################################################################
#March 12, 2024
# load libraries
library('pheatmap')
library(ggplot2)
li... |
6db8b8a5ef1c294bd4c5beb9ac7a5bec323770861ad391c70eccbaff68e5f7ed | R | 9,404 | 242 | ---
title: "Figure 6"
author: "Sang LIU"
date: "`r Sys.Date()`"
output:
html_document:
code_download: TRUE
theme: united
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE)
```
## Load packages
```{r}
library(circlize)
library(nat)
library(ComplexHeatmap)
library(... |
54bb5f0caef02bc59fe7884f9143f24565053351fd5e663ad78fe7144dc1b418 | R | 9,407 | 309 | #' @title
#' Training
#' @description
#' Tranining broad class classifier
#' @param stTrain a dataframe that matches the samples with category
#' @param expTrain the expression matrix
#' @param dLevel the name of the column that contains categories
#' @param colName_samp the name of the column that contains sample name... |
65cfed657264ecec402a2698ba5aa631607aca41ab9c22b19cf9e180bceb6187 | R | 9,455 | 280 | ---
title: "Batch effects of conversion efficiency"
date: 2015-10-23
author: Joyce Hsiao & PoYuan Tung
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
# opts_chunk$set(cache = TRUE)
```
## Obje... |
37b04deb1b7e36ed7211664824c37d5c602c5f79e736bbef850a1159ed0272c8 | R | 9,484 | 246 | outputDiagGRM = function(
GRMdiagfile = "",
GRMdiagSamplefile = "",
plinkFile = "",
phenoFile = "",
phenoCol = "",
traitType = "binary",
invNormalize = FALSE,
covarColList = NULL,
qCovarCol = NULL,
sam... |
03ad3e80884a43799c4820c056ed6206c74d7fa25a57a11a03b7057ba09ad38d | R | 9,489 | 273 | ---
title: "Revision PRM"
output: html_document
date: "2024-07-02"
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
dir <- "/wins/ori/Antonio/SpectroDive/PRM_Revision_Science_Paper_WholeBrain/SecondTry_Good"
#Create all the colors
col_code <- c("Transcriptome"="#377EB8",
"Proteome"="#E4... |
69fd0ea07b774ef5c5102500c2fd4d98b1dca5d49dfb574287d7a6c9b711cc69 | R | 9,495 | 289 | # Spatial distirbution between clusters
# input data:
# - all_cells-clusters.csv (SIMPLI output)
# - UMAPs.rds (generated in 2b. UMAPs of clusters)
# - clusters_labels.csv (metadata)
##### 0. Load libraries ######
#install.packages("tidyverse")
library(tidyverse)
library(reshape)
library(data.table)
library(dplyr)
l... |
948f577bc7b2fd3491f1558a5767e145d8c285fa0acbc57f712852f37f604738 | R | 9,543 | 246 | ---
title: "Setup for using ngsplot"
date: 2015-03-07
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
opts_chunk$set(cache = FALSE)
```
[ngsplot][] calculates coverage of genomic regions.
It pr... |
724e518b09b32b6a1144ece47bc37d7fa6082988b43cdf12d11baf1c81430c18 | R | 9,546 | 281 | ---
title: "metaG_Figs"
author: "SRomano"
output: html_document
editor_options:
chunk_output_type: console
---
# load packages
```{r}
library(ggplot2)
library(dplyr)
```
# Load the data
```{r}
# clr
s5<-readRDS("/metaG/R_analyses/Taxonomy/RDS/Single_5per_log.rds")
s10<-readRDS("/metaG/R_analyses/Taxonomy/RDS/Singl... |
ea1a61ae54c1cd6bf6ea245b4e13039ef625f639ac8dea0fe990f7611d8ab34d | R | 9,551 | 255 | #!/usr/bin/env R
### Author: Sean Maden
###
### Get diagram of deconvolution classes from lute.
###
### 1. A. deconvolutionParam
### 2. B. referencebasedParam
### 3. C. independentbulkParam
### 4. 1. nnlsParam
### 5. 2. musicParam
### 6. 3. epicParam
### 7. 4. deconrnaseqParam
### 8. 5. music2Param
### 9. 6. music2Par... |
4704cc9505f5e7e9c9729c57f3df6807f37a7fc20367ebc0209e44862f3fe587 | R | 9,577 | 156 | #t-SNE plot(Fig.1D, Fig.S1C-D, Fig.2E)
library(Seurat)
library(monocle)
library(ggplot2)
DimPlot(sce_10X_integrated, reduction = "tsne.harmony",group.by = "harmony_clusters",pt.size = 0.2)+
scale_color_manual(values=palette(c("#98F7E4","#5F72E2","#985AB1",
"#E6A0EA","#FDC471","... |
dd95e55eca8671d62377f467e4dcc62ae89107d629d7b8cf581576a4c22ff90d | R | 9,580 | 214 | #### This code generates the middle section of figure 2
#panels A and B were generated separately in Matlab
#panels H and I were generated separately in Python
#load relevant packages
library('broom')
library('lme4')
library('pracma')
#panel C: HD encoding accuracy
#load data
offset_precision_data <- r... |
5af00fb454b7996f629cb4157375be640a5e395ed7aabd452dfa2bdfaf3d9ee2 | R | 9,587 | 258 | # sif=/mnt/data1/public/singularity/dcibioinformaticsR-v2.1.sif
# wd=/mnt/data1/workspace/Anders/MelBrM
# rtmp=/mnt/data1/workspace/Methods/Containers/MissingPackages/v2.1:/rtmp
# singularity exec \
# --containall \
# --no-home \
# --bind ${wd}:${wd}:rw \
# --bind ${rtmp} \
# ${sif} \
# R
set.s... |
ad910c7a2494ae6ed291628cb4ec88a0c59ddd58b2fbd6ee5b9bf4e909eee7e1 | R | 9,597 | 257 | ---
title: "CDV LOSO"
author: "SRomano"
output: html_document
editor_options:
chunk_output_type: console
---
# Load packages
```{r setup}
library(phyloseq)
library(dplyr)
library(mlr3)
library(SIAMCAT)
require(mlr3extralearners)
library(ggplot2)
source("/Scripts/Cross_study_validation.r")
source("/Scripts/Siamcat... |
27729be44691eeecc0d16f8f4e5952fda7b257f9caf12f25917d7fed9fce367c | R | 9,626 | 241 | #Script to create Figure 1
library(Seurat)
library(tidyverse)
library(gdata)
library(slingshot)
library(RColorBrewer)
library(sctransform)
library(glmGamPoi)
library(cowplot)
set.seed(1000)
#Ascl1 data ----
#pseudotime construction using PCA for Ascl1 NSCs ----
load(file = "1st_submission/seurat_objects/Ascl1_qNSCs.... |
8dc6106ddf1152cf3c3bae548860872ed63f2f1ffd4ad949491fa6e60398a748 | R | 9,637 | 302 | ---
title: "Normalize coefficients of variation"
author: "Joyce Hsiao"
date: 2015-10-15
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
library(knitr)
opts_chunk$set(message = FALSE, warning = ... |
3abc1bc1665bdcdc3ca3d1a9898fd922f1bd21cd2273b46989674f68d72a4256 | R | 9,646 | 229 | #Example pipeline for aligning our results across datasets:
#Megan Hagenauer
#July 27 2026
############
#Goals:
#Each dataset has differential expression results from a slightly different list of genes
#Depending on the exact tissue dissected, the sensitivity of the transcriptional profiling platform, the representat... |
4aacf7ef91f5de01f587a762ffd5369e991137c8347aad43596c9aa551290aa2 | R | 9,653 | 256 | #'@export
#'@title collapseMlist
#'@description Takes in input a list of multiexperiment. In this case the complete
#'mlist containing all the datasets, and a vector containing the names of the
#'dataset you want to use, plus some other parameter coming from the shiny app
#'control panel. It collapses the results in a... |
dfd8117a7e568c3894d0ab774bba8c35b4d3a095e883b3236713b49596b30ebd | R | 9,659 | 296 | ---
title: "Bortezomib Old"
output: html_document
date: "2024-06-25"
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
## Load Settings
```{r}
col_code_aging <- c(rev(RColorBrewer::brewer.pal(n = 4,"PiYG"))[c(3,1)],"#86b8e1","#e1868b",
rev(RColorBrewer::brewer.pal(n = 4,"... |
9fcc30c028bf9ed30f023c9bfb22743be8e028bc3db613ce120d211b37b8fc96 | R | 9,666 | 294 | ---
title: "Quantify similarity between CVs"
author: "Joyce Hsiao"
date: 2015-10-31
---
**Last updated:** `r Sys.Date()`
**Code version:** `r system("git log -1 --format='%H'", intern = TRUE)`
```{r chunk-options, include=FALSE}
source("chunk-options.R")
library(knitr)
opts_chunk$set(message = FALSE, warning = FALS... |
1cc4a262a210a3e68e5f72c515be6d055442157c4006da7974dd7c5a9a0cc1d4 | R | 9,692 | 289 | ---
title: "Shared functions and formatting"
author: "Edward Wallace"
date: '2023-05-16'
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE , warning=FALSE, message=FALSE)
```
```{r load_packages, echo=FALSE}
library(tidyverse) # data wrangling, ggplot, etc.
library(reshape2) # ... |
36b84f6c57412effdf0d10ebf37f87bbbe51fb9bc1191df82ace0a576a3995a0 | R | 9,713 | 189 | #Code for generating simulations for Figure S1 of Warecki et al., 2024 ("Wolbachia infection reduces the abundance of the glutamate receptor mGluR and promotes female promiscuity and bacterial spread")
#These simulations are based on experimental data generated in Figure 1 and provided in the file "grouped.mating.assay... |
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